James T. Kwok
According to our database^{1},
James T. Kwok
authored at least 186 papers
between 1995 and 2018.
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Bibliography
2018
FastSolving QuasiOptimal LSS^{3}VM Based on an Extended Candidate Set.
IEEE Trans. Neural Netw. Learning Syst., 2018
MultiLabel Learning with Global and Local Label Correlation.
IEEE Trans. Knowl. Data Eng., 2018
Scalable Online Convolutional Sparse Coding.
IEEE Trans. Image Processing, 2018
Corrigendum to "Multilabel learning in the independent label subspaces" [Pattern Recognition Letters 97(2017) 812].
Pattern Recognition Letters, 2018
Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data.
CoRR, 2018
Power Law in Sparsified Deep Neural Networks.
CoRR, 2018
Online Convolutional Sparse Coding with SampleDependent Dictionary.
CoRR, 2018
Lossaware Weight Quantization of Deep Networks.
CoRR, 2018
Learning with Heterogeneous Side Information Fusion for Recommender Systems.
CoRR, 2018
Online Convolutional Sparse Coding with SampleDependent Dictionary.
Proceedings of the 35th International Conference on Machine Learning, 2018
Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data.
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
A Note on the Unification of Adaptive Online Learning.
IEEE Trans. Neural Netw. Learning Syst., 2017
MultiLabel learning in the independent label subspaces.
Pattern Recognition Letters, 2017
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
Journal of Machine Learning Research, 2017
LargeScale LowRank Matrix Learning with Nonconvex Regularizers.
CoRR, 2017
MultiLabel Learning with Global and Local Label Correlation.
CoRR, 2017
Accelerated and Inexact SoftImpute for LargeScale Matrix and Tensor Completion.
CoRR, 2017
Online Convolutional Sparse Coding.
CoRR, 2017
Zeroshot learning with a partial set of observed attributes.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems.
Proceedings of the TwentySixth International Joint Conference on Artificial Intelligence, 2017
Follow the Moving Leader in Deep Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017
Collaborative Filtering with Social Local Models.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017
Efficient Sparse LowRank Tensor Completion Using the FrankWolfe Algorithm.
Proceedings of the ThirtyFirst AAAI Conference on Artificial Intelligence, 2017
2016
Fast Learning with Nonconvex L12 Regularization.
CoRR, 2016
Learning of Generalized LowRank Models: A Greedy Approach.
CoRR, 2016
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
CoRR, 2016
Lossaware Binarization of Deep Networks.
CoRR, 2016
Fast Nonsmooth Regularized Risk Minimization with Continuation.
CoRR, 2016
FastandLight Stochastic ADMM.
CoRR, 2016
Aggregating Crowdsourced Ordinal Labels via Bayesian Clustering.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016
Greedy Learning of Generalized LowRank Models.
Proceedings of the TwentyFifth International Joint Conference on Artificial Intelligence, 2016
FastandLight Stochastic ADMM.
Proceedings of the TwentyFifth International Joint Conference on Artificial Intelligence, 2016
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Asynchronous Distributed SemiStochastic Gradient Optimization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
Towards Safe SemiSupervised Learning for Multivariate Performance Measures.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
Efficient Learning of Timeseries Shapelets.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
Fast Nonsmooth Regularized Risk Minimization with Continuation.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
2015
Machine Learning.
Proceedings of the Springer Handbook of Computational Intelligence, 2015
Scaling Up GraphBased Semisupervised Learning via Prototype Vector Machines.
IEEE Trans. Neural Netw. Learning Syst., 2015
LargeScale Nyström Kernel Matrix Approximation Using Randomized SVD.
IEEE Trans. Neural Netw. Learning Syst., 2015
Scalable Nonparametric LowRank Kernel Learning Using Block Coordinate Descent.
IEEE Trans. Neural Netw. Learning Syst., 2015
BayesOptimal Hierarchical Multilabel Classification.
IEEE Trans. Knowl. Data Eng., 2015
Fast Distributed Asynchronous SGD with Variance Reduction.
CoRR, 2015
Fast LowRank Matrix Learning with Nonconvex Regularization.
CoRR, 2015
Fast Second Order Stochastic Backpropagation for Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Collaborative filtering via cofactorization of individuals and groups.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Accelerated Inexact SoftImpute for Fast LargeScale Matrix Completion.
Proceedings of the TwentyFourth International Joint Conference on Artificial Intelligence, 2015
Fast LowRank Matrix Learning with Nonconvex Regularization.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015
Colorization by PatchBased Local LowRank Matrix Completion.
Proceedings of the TwentyNinth AAAI Conference on Artificial Intelligence, 2015
2014
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification.
IEEE Trans. Neural Netw. Learning Syst., 2014
Simple randomized algorithms for online learning with kernels.
Neural Networks, 2014
Selected papers from the 2011 International Conference on Neural Information Processing (ICONIP 2011).
Neurocomputing, 2014
Learning to Predict from Crowdsourced Data.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014
Fast Stochastic Alternating Direction Method of Multipliers.
Proceedings of the 31th International Conference on Machine Learning, 2014
Asynchronous Distributed ADMM for Consensus Optimization.
Proceedings of the 31th International Conference on Machine Learning, 2014
Accelerated Stochastic Gradient Method for Composite Regularization.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
Gradient Descent with Proximal Average for Nonconvex and Composite Regularization.
Proceedings of the TwentyEighth AAAI Conference on Artificial Intelligence, 2014
Accurate Integration of Aerosol Predictions by Smoothing on a Manifold.
Proceedings of the TwentyEighth AAAI Conference on Artificial Intelligence, 2014
Multilabel Classification with Label Correlations and Missing Labels.
Proceedings of the TwentyEighth AAAI Conference on Artificial Intelligence, 2014
2013
Convex and scalable weakly labeled SVMs.
Journal of Machine Learning Research, 2013
Convex and Scalable Weakly Labeled SVMs
CoRR, 2013
Fast Stochastic Alternating Direction Method of Multipliers.
CoRR, 2013
Accurate Probability Calibration for Multiple Classifiers.
Proceedings of the IJCAI 2013, 2013
Efficient Kernel Learning from Side Information Using ADMM.
Proceedings of the IJCAI 2013, 2013
Flexible Nonparametric Kernel Learning with Different Loss Functions.
Proceedings of the Neural Information Processing  20th International Conference, 2013
Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels.
Proceedings of the 30th International Conference on Machine Learning, 2013
Efficient Multilabel Classification with Many Labels.
Proceedings of the 30th International Conference on Machine Learning, 2013
Efficient Learning for Models with DAGStructured Parameter Constraints.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013
Learning from HighDimensional Data in Multitask/Multilabel Classification.
Proceedings of the 2nd IAPR Asian Conference on Pattern Recognition, 2013
2012
Efficient Sparse Modeling With Automatic Feature Grouping.
IEEE Trans. Neural Netw. Learning Syst., 2012
Bilinear Probabilistic Principal Component Analysis.
IEEE Trans. Neural Netw. Learning Syst., 2012
A brief introduction to the special issue for ISNN2010.
Neurocomputing, 2012
Convex Multitask Learning with Flexible Task Clusters
CoRR, 2012
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
Convex Multitask Learning with Flexible Task Clusters.
Proceedings of the 29th International Conference on Machine Learning, 2012
Hierarchical Multilabel Classification with Minimum Bayes Risk.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012
2011
A Hybrid PSOBFGS Strategy for Global Optimization of Multimodal Functions.
IEEE Trans. Systems, Man, and Cybernetics, Part B, 2011
Domain Adaptation via Transfer Component Analysis.
IEEE Trans. Neural Networks, 2011
Incorporating cellular sorting structure for better prediction of protein subcellular locations.
J. Exp. Theor. Artif. Intell., 2011
Structured clustering with automatic kernel adaptation.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011
Efficient Sparse Modeling with Automatic Feature Grouping.
Proceedings of the 28th International Conference on Machine Learning, 2011
MultiLabel Classification on Tree and DAGStructured Hierarchies.
Proceedings of the 28th International Conference on Machine Learning, 2011
Time and space efficient spectral clustering via column sampling.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011
2010
Incorporating the loss function into discriminative clustering of structured outputs.
IEEE Trans. Neural Networks, 2010
Clustered Nyström method for large scale manifold learning and dimension reduction.
IEEE Trans. Neural Networks, 2010
Simplifying mixture models through function approximation.
IEEE Trans. Neural Networks, 2010
Fast and accurate kernel density approximation using a divideandconquer approach.
Journal of Zhejiang University  Science C, 2010
Text detection in images using sparse representation with discriminative dictionaries.
Image Vision Comput., 2010
Spectral and Semidefinite Relaxation of the CLUHSIC Algorithm.
Proceedings of the SIAM International Conference on Data Mining, 2010
Manifold regularization for structured outputs via the joint kernel.
Proceedings of the International Joint Conference on Neural Networks, 2010
Making LargeScale Nyström Approximation Possible.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
Online multiple instance learning with no regret.
Proceedings of the TwentyThird IEEE Conference on Computer Vision and Pattern Recognition, 2010
CostSensitive SemiSupervised Support Vector Machine.
Proceedings of the TwentyFourth AAAI Conference on Artificial Intelligence, 2010
2009
Maximum Margin Clustering Made Practical.
IEEE Trans. Neural Networks, 2009
Building Sparse MultipleKernel SVM Classifiers.
IEEE Trans. Neural Networks, 2009
Maximum Penalized Likelihood Kernel Regression for Fast Adaptation.
IEEE Trans. Audio, Speech & Language Processing, 2009
DensityWeighted Nyström Method for Computing Large Kernel Eigensystems.
Neural Computation, 2009
Tighter and Convex Maximum Margin Clustering.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009
Multiple Kernel Clustering.
Proceedings of the SIAM International Conference on Data Mining, 2009
A Convex Method for Locating Regions of Interest with Multiinstance Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009
Accelerated Gradient Methods for Stochastic Optimization and Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
Domain Adaptation via Transfer Component Analysis.
Proceedings of the IJCAI 2009, 2009
Prototype vector machine for large scale semisupervised learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
Semisupervised learning using label mean.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
Maximum Margin Clustering with Multivariate Loss Function.
Proceedings of the ICDM 2009, 2009
Accelerated Gradient Method for Multitask Sparse Learning Problem.
Proceedings of the ICDM 2009, 2009
Unsupervised Maximum Margin Feature Selection with manifold regularization.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009
2008
MatrixVariate Factor Analysis and Its Applications.
IEEE Trans. Neural Networks, 2008
LargeScale Maximum Margin Discriminant Analysis Using Core Vector Machines.
IEEE Trans. Neural Networks, 2008
Improved Nyström lowrank approximation and error analysis.
Proceedings of the Machine Learning, 2008
Transferring Localization Models across Space.
Proceedings of the TwentyThird AAAI Conference on Artificial Intelligence, 2008
Transfer Learning via Dimensionality Reduction.
Proceedings of the TwentyThird AAAI Conference on Artificial Intelligence, 2008
2007
A Class of SingleClass Minimax Probability Machines for Novelty Detection.
IEEE Trans. Neural Networks, 2007
Face recognition using spectral features.
Pattern Recognition, 2007
SVDDBased Pattern Denoising.
Neural Computation, 2007
Surrogate maximization/minimization algorithms and extensions.
Machine Learning, 2007
Endtoend privacy control in service outsourcing of human intensive processes: A multilayered Web service integration approach.
Information Systems Frontiers, 2007
Ensembles of Partially Trained SVMs with Multiplicative Updates.
Proceedings of the IJCAI 2007, 2007
Marginalized MultiInstance Kernels.
Proceedings of the IJCAI 2007, 2007
Maximum margin clustering made practical.
Proceedings of the Machine Learning, 2007
Simpler core vector machines with enclosing balls.
Proceedings of the Machine Learning, 2007
Adaptive Localization in a Dynamic WiFi Environment through Multiview Learning.
Proceedings of the TwentySecond AAAI Conference on Artificial Intelligence, 2007
2006
Generalized Core Vector Machines.
IEEE Trans. Neural Networks, 2006
Efficient hyperkernel learning using secondorder cone programming.
IEEE Trans. Neural Networks, 2006
Multidimensional Vector Regression for Accurate and LowCost Location Estimation in Pervasive Computing.
IEEE Trans. Knowl. Data Eng., 2006
Embedded kernel eigenvoice speaker adaptation and its implication to reference speaker weighting.
IEEE Trans. Audio, Speech & Language Processing, 2006
Modelbased transductive learning of the kernel matrix.
Machine Learning, 2006
Simplifying Mixture Models through Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
LargeScale Sparsified Manifold Regularization.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
Efficient kernel feature extraction for massive data sets.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006
Learning the Kernel in Mahalanobis OneClass Support Vector Machines.
Proceedings of the International Joint Conference on Neural Networks, 2006
WaveletBased Feature Extraction for Microarray Data Classification.
Proceedings of the International Joint Conference on Neural Networks, 2006
Efficient Classification of Multilabel and Imbalanced Data using MinMax Modular Classifiers.
Proceedings of the International Joint Conference on Neural Networks, 2006
Multimodal Registration using the Discrete Wavelet Frame Transform.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006
Gene Feature Extraction Using TTest Statistics and Kernel Partial Least Squares.
Proceedings of the Neural Information Processing, 13th International Conference, 2006
Blockquantized kernel matrix for fast spectral embedding.
Proceedings of the Machine Learning, 2006
Locally adaptive classification piloted by uncertainty.
Proceedings of the Machine Learning, 2006
A regularization framework for multipleinstance learning.
Proceedings of the Machine Learning, 2006
Facial Image Reconstruction by SVDDBased Pattern Denoising.
Proceedings of the Advances in Biometrics, International Conference, 2006
Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006
Diversified SVM Ensembles for Large Data Sets.
Proceedings of the Machine Learning: ECML 2006, 2006
Accelerated Convergence Using Dynamic Mean Shift.
Proceedings of the Computer Vision, 2006
2005
Kernel Eigenvoice Speaker Adaptation.
IEEE Trans. Speech and Audio Processing, 2005
Core Vector Machines: Fast SVM Training on Very Large Data Sets.
Journal of Machine Learning Research, 2005
Accurate and Lowcost Location Estimation Using Kernels.
Proceedings of the IJCAI05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005
Core Vector Regression for very large regression problems.
Proceedings of the Machine Learning, 2005
Position estimation for wireless sensor networks.
Proceedings of the Global Telecommunications Conference, 2005. GLOBECOM '05, St. Louis, Missouri, USA, 28 November, 2005
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005
Very Large SVM Training using Core Vector Machines.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005
Towards endtoend privacy control in the outsourcing of marketing activities: a web service integration solution.
Proceedings of the 7th International Conference on Electronic Commerce, 2005
2004
Fusing images with different focuses using support vector machines.
IEEE Trans. Neural Networks, 2004
The preimage problem in kernel methods.
IEEE Trans. Neural Networks, 2004
Dissimilarity learning for nominal data.
Pattern Recognition, 2004
Speedup of kernel eigenvoice speaker adaptation by embedded kernel PCA.
Proceedings of the INTERSPEECH 2004, 2004
Bayesian inference for transductive learning of kernel matrix using the TannerWong data augmentation algorithm.
Proceedings of the Machine Learning, 2004
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model.
Proceedings of the Machine Learning, 2004
A study of various composite kernels for kernel eigenvoice speaker adaptation.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004
Incremental PCA based face recognition.
Proceedings of the 8th International Conference on Control, 2004
Efficient Hyperkernel Learning Using SecondOrder Cone Programming.
Proceedings of the Machine Learning: ECML 2004, 2004
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo.
Proceedings of the Nineteenth National Conference on Artificial Intelligence, 2004
2003
Linear dependency between ε and the input noise in εsupport vector regression.
IEEE Trans. Neural Networks, 2003
Texture classification using the support vector machines.
Pattern Recognition, 2003
Mining customer product ratings for personalized marketing.
Decision Support Systems, 2003
Eigenvoice Speaker Adaptation via Composite Kernel PCA.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003
Parametric Distance Metric Learning with Label Information.
Proceedings of the IJCAI03, 2003
The PreImage Problem in Kernel Methods.
Proceedings of the Machine Learning, 2003
Learning with Idealized Kernels.
Proceedings of the Machine Learning, 2003
2002
Multifocus image fusion using artificial neural networks.
Pattern Recognition Letters, 2002
Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images.
Information Fusion, 2002
Improving DeNoising by Coefficient DeNoising and Dyadic Wavelet Transform.
Proceedings of the 16th International Conference on Pattern Recognition, 2002
Fusing Images with Multiple Focuses Using Support Vector Machines.
Proceedings of the Artificial Neural Networks, 2002
2001
Combination of images with diverse focuses using the spatial frequency.
Information Fusion, 2001
Linear Dependency between epsilon and the Input Noise in epsilonSupport Vector Regression.
Proceedings of the Artificial Neural Networks, 2001
Applying the Bayesian Evidence Framework to \nu Support Vector Regression.
Proceedings of the Machine Learning: EMCL 2001, 2001
Bayesian Support Vector Regression.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001
2000
The evidence framework applied to support vector machines.
IEEE Trans. Neural Netw. Learning Syst., 2000
Rival Penalized Competitive Learning for ModelBased Sequence Clustering.
Proceedings of the 15th International Conference on Pattern Recognition, 2000
1999
Moderating the outputs of support vector machine classifiers.
IEEE Trans. Neural Networks, 1999
Moderating the outputs of support vector machine classifiers.
Proceedings of the International Joint Conference Neural Networks, 1999
Integrating the evidence framework and the support vector machine.
Proceedings of the ESANN 1999, 1999
1998
Automated Text Categorization Using Support Vector Machine.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998
1997
Objective functions for training new hidden units in constructive neural networks.
IEEE Trans. Neural Networks, 1997
Constructive algorithms for structure learning in feedforward neural networks for regression problems.
IEEE Trans. Neural Networks, 1997
1996
Use of bias term in projection pursuit learning improves approximation and convergence properties.
IEEE Trans. Neural Networks, 1996
Bayesian Regularization in Constructive Neural Networks.
Proceedings of the Artificial Neural Networks, 1996
1995
Improving the approximation and convergence capabilities of projection pursuit learning.
Neural Processing Letters, 1995